Embodiments of the invention relate generally to the field of magnetic resonance (MR) imaging, and more specifically to a method and system for reconstructing an MR image.
Magnetic resonance imaging (MRI) is a medical imaging technique most commonly used in radiology to visualize internal structures and functions of patients or objects. Typically, MRI uses a powerful magnetic field to magnetize protons of water in the body or any parts thereof. Consequent to the magnetization, the protons are aligned in the direction of the magnetic field. Another radio-frequency electromagnetic field is then briefly turned on that enables the protons to absorb some energy of the radio-frequency (RF) electromagnetic field. When the radio-frequency electromagnetic field is turned off, the protons release the energy at a radio-frequency which can be detected by a scanner. The position of protons in the body is then encoded by gradient coils. The gradient coils spatially encode the positions of protons by varying the magnetic field linearly across the body or any parts thereof. RF receive coils acquire the encoded information in the form of magnetic resonance (MR) signals that may be used to reconstruct an image.
Parallel imaging is one field of technology used in MRI for the reconstruction of images utilizing MR signals. In parallel imaging, the MR signals are received in parallel from a plurality of surface RF coils that are then processed for reconstruction of an image. Parallel acquisition of the MR signals substantially reduces acquisition time of MR signals. Unfortunately, parallel imaging leads to aliasing artifacts and increased noise in the reconstructed image.
Compressed sensing is another field of technology used in MRI for acquisition and reconstruction of images utilizing MR signals. Specifically, compressed sensing enables sampling of the MR signals at a rate lower than Nyquist rate, and still achieves substantially accurate reconstruction of the images. The speed of acquisition of the MR signals can be further increased by combining compressed sensing and parallel imaging.
Thus, it is highly desirable to develop a method and system that enables high-speed acquisition of images with reduced noise and aliasing artifacts in the MR signals leading to high-speed reconstruction of images. More particularly, there is a need for a distributed compressed sensing technique that substantially circumvents the shortcomings of compressed sensing and parallel imaging by combining compressed sensing and parallel imaging.